Jocelyn CHANUSSOT
Professeur Grenoble-INP
Equipe SIGnal iMAge PHYsique
Département Images et Signal
En délégation au 01/09/2019 au 31/08/2021
ME CONTACTER / CONTACT ME
Mail : jocelyn.chanussot@gipsa-lab.grenoble-inp.fr

11 rue des mathématiques
Domaine Universitaire
BP 46
38402 Saint Martin d'Hères cedex

Bureau D1136
Tél.33 (0)4 76 82 62 73
Fax : 33 (0)4 76 57 47 90
PUBLICATIONS RECENTES / RECENT PUBLICATIONS
Les derniéres publications de la collection Gipsa dans HAL

Braids of partitions for the hierarchical representation and segmentation of multimodal images

Guillaume Tochon, Mauro Dalla Mura, Miguel Angel Veganzones, Thierry Géraud, Jocelyn Chanussot. Braids of partitions for the hierarchical representation and segmentation of multimodal images. Pattern Recognition, Elsevier, 2019, 95, pp.162-172. ⟨10.1016/j.patcog.2019.05.029⟩. ⟨hal-02307542⟩

Fourier-based Rotation-invariant Feature Boosting: An Efficient Framework for Geospatial Object Detection

Xin Wu, Danfeng Hong, Jocelyn Chanussot, Yang Xu, Ran Tao, et al.. Fourier-based Rotation-invariant Feature Boosting: An Efficient Framework for Geospatial Object Detection. 2019. ⟨hal-02307442⟩

An Introduction to Deep Morphological Networks

Keiller Nogueira, Jocelyn Chanussot, Mauro Dalla Mura, William Robson Schwartz, Jefersson A. Dos Santos. An Introduction to Deep Morphological Networks. 2019. ⟨hal-02307437⟩

Assessment of Hyperspectral Sharpening Methods for the Monitoring of Natural Areas Using Multiplatform Remote Sensing Imagery

Javier Marcello, Edurne Ibarrola-Ulzurrun, Consuelo Gonzalo-Martin, Jocelyn Chanussot, Gemine Vivone. Assessment of Hyperspectral Sharpening Methods for the Monitoring of Natural Areas Using Multiplatform Remote Sensing Imagery. IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2019, 57 (10), pp.8208-8222. ⟨10.1109/TGRS.2019.2918932⟩. ⟨hal-02307510⟩

Dynamic Multicontext Segmentation of Remote Sensing Images Based on Convolutional Networks

Keiller Nogueira, Mauro Dalla Mura, Jocelyn Chanussot, William Robson Schwartz, Jefersson Alex dos Santos. Dynamic Multicontext Segmentation of Remote Sensing Images Based on Convolutional Networks. IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2019, 57 (10), pp.7503-7520. ⟨10.1109/TGRS.2019.2913861⟩. ⟨hal-02307468⟩

An Improved Stationarity Test Based on Surrogates

Douglas Baptista de Souza, Jocelyn Chanussot, Anne-Catherine Favre, Pierre Borgnat. An Improved Stationarity Test Based on Surrogates. IEEE Signal Processing Letters, Institute of Electrical and Electronics Engineers, 2019, 26 (10), pp.1431-1435. ⟨10.1109/LSP.2019.2931150⟩. ⟨hal-02307460⟩

Superresolution Land Cover Mapping Based on Pixel-, Subpixel-, and Superpixel-Scale Spatial Dependence With Pansharpening Technique

Peng Wang, Lei Zhang, Gong Zhang, Hui Bi, Mauro Dalla Mura, et al.. Superresolution Land Cover Mapping Based on Pixel-, Subpixel-, and Superpixel-Scale Spatial Dependence With Pansharpening Technique. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2019, pp.1-17. ⟨10.1109/JSTARS.2019.2939670⟩. ⟨hal-02307449⟩

StfNet : A Two-Stream Convolutional Neural Network for Spatiotemporal Image Fusion

Xun Liu, Chenwei Deng, Jocelyn Chanussot, Danfeng Hong, Baojun Zhao. StfNet : A Two-Stream Convolutional Neural Network for Spatiotemporal Image Fusion. IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2019, 57 (9), pp.6552-6564. ⟨10.1109/TGRS.2019.2907310⟩. ⟨hal-02307398⟩

HyperPNN: Hyperspectral Pansharpening via Spectrally Predictive Convolutional Neural Networks

Lin He, Jiawei Zhu, Jun Li, Antonio Plaza, Jocelyn Chanussot, et al.. HyperPNN: Hyperspectral Pansharpening via Spectrally Predictive Convolutional Neural Networks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2019, 12 (8), pp.3092-3100. ⟨10.1109/JSTARS.2019.2917584⟩. ⟨hal-02307371⟩

Hyperspectral Anomaly Detection via Global and Local Joint Modeling of Background

Zebin Wu, Wei Zhu, Jocelyn Chanussot, Yang Xu, Stanley Osher. Hyperspectral Anomaly Detection via Global and Local Joint Modeling of Background. IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2019, 67 (14), pp.3858-3869. ⟨10.1109/TSP.2019.2922157⟩. ⟨hal-02307409⟩

ENCADREMENT DE THESES / PhD THESIS SUPERVISED

Grenoble Images Parole Signal Automatique laboratoire

UMR 5216 CNRS - Grenoble INP - Université Joseph Fourier - Université Stendhal